The present status of HDTV in Europe and the concept of an evolutionary introduction of HDTV broadcasting is described. Corresponding HDTV standards and studio technologies are outlined. Analog transmission techniques like HD-MAC as well as coding techniques for digital transmission are presented. Also some informations about investigations for non-broadcast applications are given.

Principal Component Analysis (PCA) is a useful technique in feature extraction and data compression. It can be formulated as a statistical constrained maximization problem, whose solution is given by unit eigenvectors of the data covariance matrix. In a practical application like image compression, the problem can be solved numerically by a corresponding gradient ascent maximization algorithm. Such on-line algoritms can be good alternatives due to their parallelism and adaptivity to input data. The algorithms can be implemented in a local and homogeneous way in learning neural networks. One example is the Subspace Network. It is a regular layer of parallel artificial neurons with a learning rule that is completely homogeneous with respect to the neurons. However, due to the complete homogeneity, the learning rule does not converge to the unique basis given by the dominant eigenvectors, but any basis of this eigenvector subspace is possible. In many applications like data compression, the subspace is not sufficient but the actual eigenvectors or PCA coefficient vectors are needed. A new criterion, called the Weighted Subspace Criterion, is proposed, which makes a small symmetry-breaking change to the Subspace Criterion. Only the true eigenvectors are solutions. Making the corresponding change to the learning rule of the Subspace Network gives a modified learning rule, which can be still implemented on a homogeneous network architecture. In learning, the weight vectors will tend to the true eigenvectors.

Artificial neurons and neural networks have been shown to perform Principal Component Analysis (PCA) when gradient ascent learning rules are used, which are related to the constrained maximization of statistical objective functions. Due to their parallelism and adaptivity to input data, such algorithms and their implementations in neural networks are potentially useful in feature extraction and data compression. In the companion paper(9), two such learning rules were derived from two criteria, the Subspace Criterion and the Weighted Subspace Criterion. It was shown that the only solutions to the latter problem are dominant eigenvectors of the data covariance matrix, which are the basis vectors of PCA. It was suggested by a simulation that the corresponding learning algorithm converges to these eigenvectors. A homogeneous neural network implementation was proposed for the algorithm. The learning algorithm is analyzed here in detail and it is shown that it can be approximated by a continuous-time differential equation that is obtained by averaging. It is shown that the asymptotically stable limits of this differntial equation are the eigenvectors. The neural network learning algorithm is further extended to a case in which each neuron has a sigmoidal nonlinear feedback activity function. Then no parameters specific to each neuron are needed, and the learning rule is fully homogeneous.

Efficient probabilistic decision trees are required in various application areas such as character recognition. This paper presents a polynomial-time approximate algorithm for designing a probabilistic decision tree. The obtained tree is near-optimal for the cost, defined as the weighted sum of the expected test execution time and expected loss. The algorithm is advantageous over other reported heuristics from the viewpoint that the goodness of the solution is theoretically guaranteed. That is, the relative deviation of the obtained tree cost from the exact optimum is not more than a positive constant ε, which can be set arbitrarily small. When the given loss function is Hamming metric, the time efficiency is further improved by using the information theoretical lower bound on the tree cost. The time efficiency of the algorithm and the accuracy of the solutions were evaluated through computational experiments. The results show that the computing time increases very slowly with an increase in problem size and the relative error of the obtained solution is much less than the upper bound ε for most problems.

This paper presents a destributed algorithm that uses weak copy consistency to create mutual exclusion in a distributed computer system. The weak copy consistency is deduced from the uncertainty of state which occurs due to the finite and unpredictable communication delays in a distributed environment. Also the method correlates outdated state information to current state. The average number of messages to enter critical section in the algorithm is n/2 to n messages where n is the number of sites. We show that the algorithm achieves mutual exclusion and the fairness and liveness of the algorithm is proven. We study the performance of the algorithm by simulation technique.

This paper proposes a Mean-Separated and Normalized Vector Quantizer with edge-Adaptive Feedback estimation and variable bit rates (AFMSN-VQ). The basic idea of the AFMSN-VQ is to estimate the statistical parameters of each coding block from its previous coded blocks and then use the estimated parameters to normalize the coding block prior to vector quantization. The edge-adaptive feedback estimator utilizes the interblock correlations of edge connectivity and gray level continuity to accurately estimate the mean and standard deviation of the coding block. The rate-variable VQ is to diminish distortion nonuniformity among image blocks of different activities and to improve the reconstruction quality of edges and contours to which the human vision is sensitive. Simulation results show that up to 2.7dB SNR gain of the AFMSN-VQ over the non-adaptive FMSN-VQ and up to 2.2dB over the 1616 ADCT can be achieved at 0.2-1.0 bit/pixel. Furthermore, the AFMSN-VQ shows a comparable coding performance to ADCT-VQ and A-PE-VQ.

Threre are two types of nonlinear associative silicon retinas. One is a sparse Hopfield type neural network which is called a H-type retina and the other is its dual network which is called a DH-type retina. The input information sequences of H-type and HD-type retinas are given by nodes and links as voltages and currents respectively. The error correcting capacity (minimum basin of attraction) of H-type and DH-type retinas is decided by the minimum numbers of links of cutset and loop respectively. The operation principle of the regeneration is based on the voltage or current distribution of the neural field. The most important nonlinear operation in the retinas is a dynamic quantization to decide the binary value of each neuron output from the neighbor value. Also, the edge is emphasized by a line-process. The rates of compression of H-type and DH-type retinas used in the simulation are 1/8 and (2/3) (1/8) respectively, where 2/3 and 1/8 mean rates of the structural and binarizational compression respectively. We could have interesting and significant simulation results enough to make a chip.

A theoretical conjecture on fractal dimensions of a dendrite distribution in neural networks is presented on the basis of the dendrite tree model. It is shown that the fractal dimensions obtained by the model are consistent with the recent experimental data.

An application of wavelength conversion laser diodes (WCLDs) to a photonic cross-connect system using wavelength-division (WD) technology is presented. We propose a novel WD photonic cross-connect node architecture with multiwavelength selective filters. By using the filters, we can construct a nonblocking cross-connect switch by 2-stage connection. Next we describe the requirements to the optical devices in our switch, especially to the wavelength conversion devices in configuring a multistage connection of our switch. Finally, we have conducted the wavelength switching experiments using our wavelength conversion laser diode at a bit rate of 125Mb/s and shown its applicability to a WD photonic cross-connect system with over 3,000 channels.

This paper examines the key technologies and applications of optical frequency division multiplexing (OFDM) systems. It is clarified that a 100-channel OFDM system is feasible as a result of multichannel frequency stabilization, common optical amplification and channel selection utilizing a tunable optical filter. Transmission limitation due to fiber four-wave mixing is also described. Major functions and applications of the OFDM are summarized and the applicability of OFDM add/drop multiplexing is examined.

Binary Decision Diagrams (BDDs) and Shared Binary Decision Diagrams (SBDDs), which are improved BDDs, are useful for implementing VLSI logic design systems. Recently, these representations, which are graph representations of Boolean functions, have become popular because of their efficiency in terms of time and space. The forms of the BDD vary with the order of the input variables though they represent the same function. The size of the graphs greatly depends on the order. The variable ordering algorithm is one of the most important issues in the application of BDDs. In this paper, we consider methods which reduce the graph size by reordering input variables on a given BDD with a certain variable order. We propose the Minimum-Width Method which gives a considerably good order in a practicable time and space. In the method, the order is determined by width of BDDs as a cost function. In addition, we show the effect of combining our method with the local search method, and also describe the improvement using the threshold. Experimental results show that our method can reduce the size of BDDs remarkably for most examples. The method needs no additional information, such as the topological information of the circuit. The results can be a measure for evaluation of other ordering methods.

Networks in this paper consist of non-commensurate transmission lines with branches and branching resistors at junctions. When signals on a transmission line are divided multiple ways at the junctions of branched lines, multiple reflection waves occur by the impedance mismatching. For the analysis of multiple reflections and network design, lattice diagrams have been used so far. However, the expansions of network transfer functions provide an easier way for the same purpose as in the case of lattice diagram. The output transient responses can be directly calculated from the expansions of network transfer functions or can be numerically calculated by software such as the fast Laplace transform. Therefore, once the network transfer functions are given, calculation of transient responses can be carried out quite easily. In this paper, the expansions of network transfer functions have been derived with respect to delay elements ξi=exp(-sτi) by formularizing the propagation of multiple reflection waves, and then the multi-variable rational network transfer functions have been obtained from the expansions. As an example, a 3-port transmission line network with normalized characteristic impedances 1, 1, 6 and normalized branching resistors 1/23, 1/23, 126/23 has been taken up. As the terminal resistances at output ports can be determined from the relation of the first arriving wave to the steady state, the design of 3-port transmission line networks which will furnish output waveforms similar to the waveform of the input within given tolerances has been considered. The output waveforms have been calculated for pure terminal resistances and for the pure terminal resistances plus parasitic parallel capacitances.

It is important to develop methods of measuring radiated electromagnetic interference level that will produce identical results at all measuring locations. We have considered a number of problems which prevent the achievement of identical results, and proposed some solutions. However, agreement of measurement values adequate for practical purposes has not been achieved. After our successive studies, we finally became aware that there is a causal relationship with changes in the line-to-ground impedance of the power supply. It is presumed that power cables of AC-powered devices operate as antenna elements that produce emission. Thus changes in the power line-to-ground impedance cause variations in the radiation efficiency to produce a different EMI level. We therefore made plans to measure the values of line-to-ground impedance at the AC power outlet for the frequency range of 100kHz to 500MHz at various locations where measurements are made of EMI from EUT (Equipment Under Test). The impedance varies greatly between 6ohms and 2 k-ohm, not only according to the frequency, but also according to the measurement location. In such cases, the EMI level shows a different value even with the same EUT, and it usually increases-especially for vertical polarization. We have developed a new type of LISN (Line Impedance Stabilization Network or Artificial Mains Network) to stabilize the power line-to-ground impedance to get consistent measurement conditions. The LISN consists of feed-through capacitors and an disk type RF resistor. The measurements confirm the consistency in the impedance value which is maintained at 50 ohms in the frequency range from 1MHz to 500MHz. Thus the newly developed LISN improves consistency of measurement values at all locations, while it was difficult to obtain good correlation before employing the LISN. We feel confident that incorporation of the method discussed here in the pertinent technical standards of EMI measurements, such as CISPR, would lead to a major improvement in getting consistent measurements values.

Dynamic behavior of a distributed parameter system described by the one-dimensional wave equation with a nonlinear boundary condition is examined in detail using a graphical method proposed by Witt on a digital computer. The bifurcation diagram, homoclinic orbit and one-dimensional map are obtained and examined. Results using an analog simulator are introduced and compared with that of the graphical method. The discrepancy between these results is considered, and from the comparison among the bifurcation diagrams obtained by the graphical method, it is denoted that the energy dissipation in the system considerably restrains the chaotic state in the bifurcation process.

This paper outlines an approach for specifying emissions performance at the component level. The objective is to move towards an industry specification for radiated emissions from large integrated circuits in order to facilitate cost effective system design for EMI compliance. Simple models of the mechanisms of direct chip radiation are provided based on the physical and electrical structure of large integrated circuits. These models lead to simple algorithms for estimating the total IC radiation based on IC design parameters. These models can be related to proposed emissions limits based on the desired application of the IC. Finally a measurement methodology is described which permits evaluation of the IC's relative to the limits and provides the information required to make detailed simulation models.

A Discrete Event System (DES) is a system that is modeled by a finite automaton. A Cooperating Discrete Event System (CDES) is a distributed system which consists of several local DESs which are synchronized with each other to accomplish its own goal. This paper describes the automatic synthesis of a CDES from a modular temporal logic specification. First, MPTS (Modular Practical Temporal Specification language) is proposed in which the new features (modular structure and domain specification) are appended to temporal logic. To overcome the "state explosion problem", which occurs in generating a global automaton in former synthesis methods using temporal logic, a compositional synthesis is proposed where automata are reduced at every composition step.

We propose a new distributed signal (analog or digital) transmission system which has the immunity against the noisy channel. An information signal in transmitter is distributed by distributor and the distributed signal is transmitted. Received signal is reconstructed by the inverse distributor in receiver. In this system, an impulsive interference noise which disturbs the transmission signal in the channel passes decoder only, and this interference noise is distributed by the inverse distributor while the transmitted signal is reconstructed. Some appended signals make it possible to estimate the noise components which inversely distributed with the Fourier transformation as the distributor. Basing upon this principle, the transmission system will have an ability to suppress the impulsive interference, and the channel will have high noise immunity. The construction of receiver which can eliminate the impulsive noise is derived.

Mechanism for radiation phenomenon caused by a finite-length transmission line is discussed. Coupling of an external wave to a transmission line has been studied by using a circuit concept because of a TEM transmission. Since the relationship between coupling and radiation is reciprocal, radiation can be treated by using the circuit concept. It is shown that the equations obtained by using the field theory are quite coincident with those by the circuit theory. From the resultant, it can be concluded that the radiated fields are composed of those by the line current of TEM and the terminal currents. A method for an application of the circuit concept to radiation due to a trace on a printed circuit board is studied by comparing the experimental results.

In two-dimensional simulation of thin-base RHET, we combined three different simulation methods--the Schrödinger equation, the Monte Carlo simulation, and two-dimensional device simulation within a drift and diffusion model. We found that, in the thin-base RHET, the potential distribution differs from that expected from the thick-base RHET. In the thin-base RHET, the potential of the intrinsic base region does not equal that of the base electrode because the intrinsic base region is depleted and the negative emitter voltage (VEB0) raises the potential of both the intrinsic base and the nondoped region under the intrinsic base. There are also modified by the collector voltage. We also show emitter current-voltage characteristics, transfer ratio, and transit time calculated using this method and compare them with results for the one-dimensional case.

The objective of this paper is to provide an overview of the recent developments in the area of speech processing and in particular in the fields of speech coding and speech recognition. The speech coding review covers DPCM coders, model-based vocoders, waveform coders, and hybrid coders. The hybrid coders are described in some detail since they are the subject of current research. Our treatment of speech recognition techniques concentrates on the methodologies for voice recognition and the progress made in speaker independent recognition. In addition, we describe the efforts towards commercial deployment of this technology.